Published on in Vol 9, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24352, first published .
Using Acoustic Speech Patterns From Smartphones to Investigate Mood Disorders: Scoping Review

Using Acoustic Speech Patterns From Smartphones to Investigate Mood Disorders: Scoping Review

Using Acoustic Speech Patterns From Smartphones to Investigate Mood Disorders: Scoping Review

Journals

  1. Kim A, Jang E, Lee S, Choi K, Park J, Shin H. Automatic Depression Detection Using Smartphone-Based Text-Dependent Speech Signals: Deep Convolutional Neural Network Approach. Journal of Medical Internet Research 2023;25:e34474 View
  2. Tonn P, Seule L, Degani Y, Herzinger S, Klein A, Schulze N. Digital Content-Free Speech Analysis Tool to Measure Affective Distress in Mental Health: Evaluation Study. JMIR Formative Research 2022;6(8):e37061 View
  3. Martínez-Nicolás I, Martínez-Sánchez F, Ivanova O, Meilán J. Reading and lexical–semantic retrieval tasks outperforms single task speech analysis in the screening of mild cognitive impairment and Alzheimer's disease. Scientific Reports 2023;13(1) View
  4. Gerczuk M, Triantafyllopoulos A, Amiriparian S, Kathan A, Bauer J, Berking M, Schuller B. Zero-shot personalization of speech foundation models for depressed mood monitoring. Patterns 2023;4(11):100873 View
  5. Calà F, Frassineti L, Sforza E, Onesimo R, D’Alatri L, Manfredi C, Lanata A, Zampino G. Artificial Intelligence Procedure for the Screening of Genetic Syndromes Based on Voice Characteristics. Bioengineering 2023;10(12):1375 View